Novel computer vision analysis of nasal shape in children with unilateral cleft lip. Issue 1 (January 2018) - Mercan, Ezgi; Morrison, Clinton S.; Stuhaug, Erik; Shapiro, Linda G.; Tse, Raymond W.
Abstract: Background: Optimization of treatment of the unilateral cleft lip nasal deformity (uCLND) is hampered by lack of objective means to assess initial severity and changes produced by treatment and growth. The purpose of this study was to develop automated 3D image analysis specific to the uCLND; assess the correlation of these measures to esthetic appraisal; measure changes that occur with treatment and differences amongst cleft types. Methods: Dorsum Deviation, Tip-Alar Volume Ratio, Alar-Cheek Definition, and Columellar Angle were assessed using computer-vision techniques. Subjects included infants before and after primary cleft lip repair (N = 50) and children aged 8–10 years with previous cleft lip (N = 50). Two expert surgeons ranked subjects according to esthetic nose appearance. Results: Computer-based measurements strongly correlated with rankings of infants pre-repair (r = 0.8, 0.75, 0.41 and 0.54 for Dorsum Deviation, Tip-Alar Volume Ratio, Alar-Cheek Definition, and Columellar Angle, p < 0.01) while all measurements except Alar-Cheek Definition correlated moderately with rankings of older children post-repair (r ∼ 0.35, p < 0.01). Measurements were worse with greater severity of cleft type but improved following initial repair. Abnormal Dorsum Deviation and Columellar Angle persisted after surgery and were more severe with greater cleft type. Conclusions: Four fully-automated measures were developed that are clinically relevant, agree with expert evaluations and can be followed through initial surgery and in older children. Computer vision analysis techniques can quantify the nasal deformity at different stages, offering efficient and standardized tools for large studies and data-driven conclusions.